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arXiv:1701.07616 · Globecom

Minimum-Distance Based Construction of Multi-Kernel Polar Codes

Valerio Bioglio, Frédéric Gabry, Ingmar Land, J.-C. Belfiore

Published Dec 1, 2017• 41 citations
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Abstract

In this paper, we propose a construction for multi-kernel polar codes based on the maximization of the minimum distance. Compared to the original construction based on density evolution, our new design shows particular advantages for short code lengths, where the polarization effect has less impact on the performance than the distances of the code. We introduce and compute the minimum-distance profile and provide a simple greedy algorithm for the code design. Compared to state-of-the-art punctured or shortened Arikan polar codes, multi-kernel polar codes with our new design show significantly improved error-rate performance.

DOI
10.1109/glocom.2017.8254147

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In this paper, we propose a construction for multi-kernel polar codes based on the maximization of the minimum distance. Compared to the original construction based on density evolution, our new design shows particular advantages for short code lengths, where the polarization effect has less impact on the performance than the distances of the code. We introduce and compute the minimum-distance profile and provide a simple greedy algorithm for the code design. Compared to state-of-the-art punctured or shortened Arikan polar codes, multi-kernel polar codes with our new design show significantly improved error-rate performance.
We propose a generalized construction for binary polar codes based on mixing multiple kernels of different sizes in order to construct polar codes of block lengths that are not only powers of integers. This results in a multi-kernel polar code with very good performance while the encoding complexity remains low and the decoding follows the same general structure as for the original Arikan polar codes. The construction provides numerous practical advantages as more code lengths can be achieved without puncturing or shortening. We observe numerically that the error-rate performance of our construction outperforms state-of-the-art constructions using puncturing methods.
We propose a generalized construction for binary polar codes based on mixing multiple kernels of different sizes in order to construct polar codes of block lengths that are not only powers of integers. This results in a multi kernel polar code with very good performance while the encoding complexity remains low and the decoding follows the same general structure as for the original Arikan polar codes. The construction provides numerous practical advantages as more code lengths can be achieved without puncturing or shortening. We observe numerically that the error-rate performance of our construction outperforms stateof the-art constructions using puncturing methods.
We propose a generalized construction for binary polar codes based on mixing multiple kernels of different sizes in order to construct polar codes of block lengths that are not only powers of integers. This results in a multi-kernel polar code with very good performance while the encoding complexity remains low and the decoding follows the same general structure as for the original Arikan polar codes. The construction provides numerous practical advantages as more code lengths can be achieved without puncturing or shortening. We observe numerically that the error-rate performance of our construction outperforms
A shortening method for large polarization kernels is presented, which results in shortened kernels with the highest error exponent if applied to kernels of size up to 32. It uses lower and upper bounds on partial distances for quick elimination of unsuitable shortening patterns.The proposed algorithm is applied to some kernels of sizes 16 and 32 to obtain shortened kernels of sizes from 9 to 31. These kernels are used in mixed-kernel polar codes of various lengths. Numerical results demonstrate the advantage of polar codes with shortened large kernels compared with shortened and punctured Arikan polar codes, and polar codes with small kernels.
Polar codes are the first class of error correction codes that achieve the Shannon channel capacity when their code length approaches infinity, but the code lengths of polar codes are limited to powers of 2. Therefore, multi-kernel polar codes are proposed, and their generator matrices are constructed from a variety of polarized kernels with different sizes. In this paper, we study the effect of different kernel orders on the channel polarization in the Gaussian approximation construction for multi-kernel polar codes. Besides, we study the minimum-distance spectrum of polarized kernels and the generator matrices of multi-kernel polar codes, and we calculate the minimum-distance spectrum for some larger kernels. We experimentally compare the advantages and disadvantages of the Gaussian approximation and minimum-distance construction. Finally, we propose a hybrid construction method which considers both the reliability and distance, and experimental results show that the proposed construction method outperforms the construction method that only considers distance and reliability.
A new family of multi-kernel polar codes are proposed. Instead of using identical matrices in each stage, assigning different constituent matrices to different virtual channels based on their properties will further improve polarization performance and error rate performance. Matrices with the same block-length can be classified based on Bhattacharyya parameters and a measure M (G) is proposed to compare their polarization performance. Construction framework and graph representation of hybrid multi-kernels are explicitly given. Numerical illustrations show that hybrid multi-kernels have better performance than previous multi-kernels.